We study firms that sell multiple differentiated substitutable products and customers whose purchase behavior follows a Nested Logit model, of which the Multinomial Logit model is a special case. Customers make purchasing decision sequentially under the Nested Logit model: they first select a nest of products and subsequently purchase a product within the selected nest. We consider the general ...

This paper develops a bias correction scheme for a multivariate normal model under a general parameterization. In the model, the mean vector and the covariance matrix share the same parameters. It includes many important regression models available in the literature as special cases, such as (non)linear regression, errors-in-variables models, and so forth. Moreover, heteroscedastic situations m...

In this study, the average surface roughness values obtained when turning AISI 4140 grade tempered steel with a hardness of 51 HRC, were modeled using fuzzy logic, artificial neural networks (ANN) and multi-regression equations. Input variables consisted of cutting speed (V), feed rate (f) and depth of cut (a) while output variable was surface roughness (Ra). Fuzzy logic and ANN models were dev...

We propose a new framework, Decision-theoretic Logic Programs (DTLPs), in the paper. DTLPs extend Probabilistic ILP models by integrating desicion-making features developed in Statistical Decision Theory area. Both decision-theoretic knowledge (eg. utilities) and probabilistic knowledge (eg. probabilities) can be represented and dealt with in DTLPs. An implementation of DTLPs using Stochastic L...

We investigate a modal logic of probability with a unary modal operator expressing that a proposition is more probable than its negation. Such an operator is not closed under conjunction, and its modal logic is therefore non-normal. Within this framework we study the relation of probability with other modal concepts: belief and action. We focus on the evolution of belief, and propose an integra...

Thanks to Craig Boutilier for valuable discussions and for comments on earlier versions of this paper .-minimax search procedure for trees containing chance nodes. [Poole, 1993a] D. Poole. Logic programming, abduction and probability: A top-down anytime algorithm for computing prior and posterior probabilities. [Poole, 1995a] D. Poole. Abducing through negation as failure: Stable models within ...

We present a reasoning about actions framework based on a sum of epistemic logic S5 and propositional dynamic logic PDL together with a ‘no forgetting’ principle, also called perfect recall. We show that in our framework an action may be decomposed into a purely ontic action followed by a purely epistemic action. We also show that the latter is completely definable in terms of simple observatio...

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. In this chapter we discuss how fuzzy logic extends the envelop of the main data mining tasks: clustering, classification, regression and association rules. We begin by presenting a formulation of the data mining using fuzzy logic attributes. Then, for each task, we pro...

New trends and the effect of key factors influence the quality of the holes produced by ECM processes. Researchers developed a fuzzy logic controller by adding intelligence to the ECM process. Maintaining optimum ECM process conditions ensures higher machining efficiency and performance. This paper presents the development of a fuzzy logic controller to add intelligence to the ECM process. An e...

The use of regression analysis to derive predictive equations for software metrics has recently been complemented by increasing numbers of studies using non-traditional methods, such as neural networks, fuzzy logic models, case-based reasoning systems, and regression trees. There has also been an increasing level of sophistication in the regression-based techniques used, including robust regres...